Warren Weaver Hall251 Mercer St.New York, NY 10012

75th Anniversary Celebration

The panel on "Games for Learning" aims to introduce the Courant Institute community to the ideas and activities of the Games for Learning Institute.

At the core of the G4LI is a partnership between computer science and learning science. We will discuss how interdisciplinary research between these two fields enables the creation of games that are effective in educating young people about concepts in mathematics and science.

The panel consists of five faculty members from the Center of Atmosphere Ocean Science within the Mathematics Department at the Courant. The members with special interests in brackets are: E. Gerber (atmosphere global circulation); R. Kleeman (predictability); A. Majda (tropical convection and predictability); O. Pauluis (tropical convection) and S. Smith (geophysical turbulence). Panelists will discuss the current big challenges in atmosphere/ocean science and how applied mathematics can help resolve these.

11:15-12:15

Mathematics, Biology, and Medicine

Biological applications of mathematics and computing at the Courant Institute include genome analysis, biomolecular structure, systems biology, embryology, immunology, neuroscience, heart physiology, internal and external biofluid dynamics, medical imaging, and population dynamics. Panel members sample this vast space, and will show examples of their work, with an eye on future challenges.

Technology and Economic Development

The Technology and Economic Development panel features a eclectic group of highly acclaimed professors from different disciplines including computer science, economics and medicine, who will be presenting their views on how technology has the potential to impact economic development in underdeveloped areas around the world. The panel will primarily focus on howappropriate technology can provide sustainable solutions to address important developmental problems including information access, healthcare, education and enabling rural markets.

During this panel discussion we explore the role of financial markets in the future. Topics include the use of mathematics in the financial industry today and tomorrow, government and regulation, ongoing research and the importance of future innovation. Where are the financial markets headed? Will trading be fully automated and run by machines in the future? When will the next crisis come – do we know?

This panel brings several renowned experts together to discuss recent trends in human and artificial intelligence. Clay Shirky, NYU Tisch ITP and Journalism faculty, is the best selling author of “Here Comes Everybody” and “Cognitive Surplus”; he is a proponent of collaborative intelligence and crowd sourcing. Paul Horn, NYU Senior Vice Provost of Research, previously head of IBM Research, originated the Watson system, which recently won the Jeopardy Challenge on CBS against the 2 best human players. Raia Hadsell is an NYU Courant alumnus and the lead architect of the robot that won the DARPA grant challenge by getting off the road and navigating through forests and wilderness. Nava Rubin, NYU Neural Science and Psychology faculty, is a human brain expert with focus on visual perception and cognition. The moderator, Chris Bregler, is an NYU Courant faculty and an expert in faking human motion and replacing human actors in Hollywood productions.

3:00-4:00

Computational Biology, Genomics, and Bioinformatics

An individual human genome can be thought of as a sequence of six billion letters over a four-character alphabet: A, C, T, and G. Together they determine the traits, or phenotype, of an individual human. Changing just a single character in this sequence can change an individual's phenotype drastically. If the change is advantageous, such a mutation can sweep through the population while nearby unrelated structures may hitch-hike with it, which makes the interpretation of genomes mathematically challenging.

Thus, to understand the genomic structure of the entire human population, one needs to analyze a vast number of genomes and associated phenotypes while paying attention to every single base of every single genome. For this reason, biologists and computer scientists focus on technologies to collect the genomic data very accurately, and algorithms to model and analyze the interrelations among the genomic data. This panel focuses on these questions, but also its relations to many other mathematical biology problems ranging from molecular dynamics for rational drug design to large-scale experiments to characterize evolutionary dynamics.